食品科学 ›› 2021, Vol. 42 ›› Issue (16): 322-327.doi: 10.7506/spkx1002-6630-20200730-396

• 安全检测 • 上一篇    下一篇

基于产地、品种和年份影响矿物元素含量的大米判别

钱丽丽,邱彦超,李殿威,符丽雪,张东杰,左锋   

  1. (1.黑龙江八一农垦大学食品学院,黑龙江 大庆 163319;2.黑龙江省杂粮加工及质量安全工程技术研究中心,黑龙江 大庆 163319;3.黑龙江省农产品加工与质量安全重点实验室,黑龙江 大庆 163319)
  • 发布日期:2021-08-27
  • 基金资助:
    黑龙江省自然科学基金联合会项目(LH2019C075)

Influence of Geographical Origin, Variety and Crop Year on Mineral Element Contents of Rice and Geographical Origin Discrimination Based on Mineral Elements

QIAN Lili, QIU Yanchao, LI Dianwei, FU Lixue, ZHANG Dongjie, ZUO Feng   

  1. (1. College of Food, Heilongjiang Bayi Agricultural University, Daqing 163319, China; 2. Heilongjiang Engineering Research Center for Coarse Cereals Processing and Quality Safety, Daqing 163319, China; 3. Key Laboratory of Agro-products Processing and Quality Safety of Heilongjiang Province, Daqing 163319, China)
  • Published:2021-08-27

摘要: 通过分析品种、年份与产地及其交互作用对大米矿物元素含量造成的差异,筛选有效特征指标,结合统计分析进行产地判别。以连续3?a(2016—2018年)在查哈阳、五常和建三江地区种植9?个品种的90?份田间试验样本为研究目标,采用电感耦合等离子体质谱仪测定样品的52?种元素。结果表明:Mg、Ca、Cr、Mn、Zn、As、Rb、Sr、Ag、Cd、Ba、La、Sm、Dy、Ho、Er、Pb、U受产地影响较大;Na、Mg、Al、Ca、Pb、U、V受年份影响较大;Na、Cr、Co、Ni、Tl、U、Mg、Al、La、Ho受品种影响较大。实验对筛选到与产地直接相关的18?种元素进行主成分分析和判别分析。6?个主成分累计贡献率80.333%。建立的判别模型对3?个产地的判别正确率均为100%,交叉验证率为100%。说明由这些元素组成的模型可以对样本实现正确判别。

关键词: 大米;矿物元素;影响因素;含量差异;统计分析;产地判别

Abstract: The effects of variety, crop year, geographical origin and their interaction on rice mineral element contents were investigated to select the characteristic mineral elements for geographical origin discrimination by statistical analysis. A total of 90 field test samples were obtained from nine varieties planted in Chahayang, Wuchang and Jiansanjiang in three consecutive years from 2016 to 2018, and 52 mineral elements in the samples were determined by inductively coupled plasma mass spectrometry (ICP-MS). The results showed that Mg, Ca, Cr, Mn, Zn, As, Rb, Sr, Ag, Cd, Ba, La, Sm, Dy, Ho, Er, Pb and U were greatly affected by geographical origins. Na, Mg, Al, Ca, Pb, U and V were significantly affected by crop years. Na, Cr, Co, Ni, Tl, U, Mg, Al, La and Ho were greatly affected by varieties. Principal component analysis (PCA) and discriminant analysis (DA) were carried out on 18 mineral elements found to be directly related to geographical origins. The cumulative contribution rate of the first six principal components was 80.333%. The accuracy of the developed discriminant model in distinguishing three producing areas was 100% and the cross validation accuracy was also 100% corroborating that the model can allow correct discrimination of samples.

Key words: rice; mineral element; factor; differences in mineral contents; statistical analysis; geographic origin discrimination

中图分类号: